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Research Papers

Dynamical Graph Models of Aircraft Electrical, Thermal, and Turbomachinery Components

[+] Author and Article Information
Matthew A. Williams

Department of Mechanical
Science and Engineering,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801
e-mail: mwillms4@illinois.edu

Justin P. Koeln

Department of Mechanical
Science and Engineering,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801
e-mail: koeln2@illinois.edu

Herschel C. Pangborn

Department of Mechanical
Science and Engineering,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801
e-mail: pangbor2@illinois.edu

Andrew G. Alleyne

Ralph & Catherine Fisher Professor
Fellow ASME
Department of Mechanical
Science and Engineering,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801
e-mail: alleyne@illinois.edu

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received December 21, 2016; final manuscript received October 18, 2017; published online December 19, 2017. Assoc. Editor: Sergey Nersesov.

J. Dyn. Sys., Meas., Control 140(4), 041013 (Dec 19, 2017) (17 pages) Paper No: DS-16-1607; doi: 10.1115/1.4038341 History: Received December 21, 2016; Revised October 18, 2017

Abstract

The current trend of electrification in modern aircraft has driven a need to design and control onboard power systems that are capable of meeting strict performance requirements while maximizing overall system efficiency. Model-based control provides the opportunity to meet the increased demands on system performance, but the development of a suitable model can be a difficult and time-consuming task. Due to the strong coupling between systems, control-oriented models should capture the underlying physical behavior regardless of energy domain or time-scale. This paper seeks to simplify the process of identifying a suitable control-oriented model by defining a scalable and broadly applicable approach to generating graph-based models of thermal, electrical, and turbomachinery aircraft components and systems. Subsequently, the process of assembling component graphs into a dynamical system graph that integrates multiple energy domains is shown. A sample electrical and thermal management system is used to demonstrate the capability of a graph model at matching the complex dynamics exhibited by nonlinear and empirically based simulation models.

References

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Figures

Fig. 1

Notional system graph with two input powers and two power sinks

Fig. 2

Comparison of counter- (a) and parallel-flow (b) heat exchanger temperature profiles for hot (subscript h) and cold (subscript c) flows

Fig. 3

Graph model of a heat exchanger

Fig. 4

Comparison of parallel-flow heat exchanger graph model and experimental data for (a) wall temperature, (b) temperature difference between the inlet and outlet of each side, and (c) power flow through the heat exchanger

Fig. 5

Infrared image showing the temperature gradient across the liquid–liquid heat exchanger

Fig. 6

Graph model of a cold plate

Fig. 7

Comparison of cold plate graph model and experimental data for (a) wall temperature and (b) fluid exit temperature

Fig. 8

Infrared image showing a 15 °C gradient across the cold plate

Fig. 9

Graph model of a tank with ambient heat loss

Fig. 10

Comparison of tank graph model and experimental data for tank temperature

Fig. 11

Graph model for electrical generator

Fig. 12

Graph model for electrical bus

Fig. 13

Graph model for constant power, current, and impedance loads

Fig. 14

Electrical system architecture for graph and simulation comparison

Fig. 15

Graph of the electrical system in Fig. 14

Fig. 16

Open loop inputs for (a) generator rotational shaft speed, (b) constant power AC and DC loads, and (c) constant current AC and DC loads

Fig. 17

Comparison of graph model and nonlinear simulation (a) generator voltage, (b) 270 V and 115 V bus voltages, (c) transient generator voltage, and (d) loads affecting bus voltage, for inputs from Fig. 17

Fig. 18

Schematic of a closed-loop ACM with a power turbine

Fig. 19

ACM graph

Fig. 20

Flight envelope points where data is collected by Matullch [27]

Fig. 21

COP by the graph model compared to Matullch [27]

Fig. 22

Temperatures of the graph model compared to Matullch [27]

Fig. 23

ACM graph with secondary fuel and bypass air heat exchangers

Fig. 24

(a) Heat rejected to the bypass air, (b) heat absorbed from the fuel by the ACM, and (c) and (d) detail showing matching transient behavior by the graph model

Fig. 25

ACM shaft speed comparison with matching transient behavior (insert)

Fig. 26

(a) Power produced by the power turbine (top) and expansion turbine (bot), (b) power consumed by the compressor, and (c) and (d) detail showing matching transient behavior by the graph model

Fig. 27

Sample aircraft electrical, thermal, and air cycle system schematic

Fig. 28

Dynamic graph model of aircraft power systems in Fig. 27

Fig. 29

Validation of graph (a) avionics wall temperature, (b) generator and engine temperatures, (c) radar temperature, (d) fuel tank #2 temperature, (e) fuel tank #1 temperature, (f) generator voltage, (g) 270 V bus voltage, and (h) 115 V bus voltage

Fig. 30

Validation of graph power flow for (a) fuel heat rejection along e43, (b) ACM heat rejection along e58, and (c) ram air heat rejection along e19

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